Research Progress on Peroxymonosulfate Activation by Copper-Based Single-Atom Catalysts for Antibiotic Removal

The persistent residue of antibiotics in aquatic environments and the subsequent global spread of antibiotic resistance (AMR) pose major threats to ecological security and public health. Advanced oxidation processes based on peroxymonosulfate (PMS) activation, which generate highly reactive species such as sulfate radicals, hydroxyl radicals, singlet oxygen, and high-valent metal-oxo species, have shown remarkable potential for the advanced treatment of antibiotic-contaminated wastewater. In recent years, copper-based single-atom catalysts (Cu SACs), featuring atomically dispersed active centers, nearly 100% atomic utilization, and highly tunable coordination microenvironments, have emerged as a research frontier in PMS activation. This review systematically summarizes the current status of antibiotic pollution and associated eco-health risks, and comprehensively discusses the main synthesis strategies for Cu SACs (e.g., MOF-pyrolysis, salt-assisted templating, nanoconfinement, multi-site synergistic systems, and biomass-derived methods) as well as structural characterization techniques. It focuses on the regulation mechanisms of PMS activation pathways through precise chemical strategies including coordination number regulation, heteroatom doping (S, P, etc.), axial/second-shell coordination engineering, and atomic inter-site spacing modulation. The competitive and synergistic relationships among radical, singlet oxygen, high-valent copper-oxo, and electron transfer pathways are systematically analyzed. Furthermore, this review evaluates the intrinsic activity, selectivity, wide pH adaptability, mineralization efficiency, catalyst stability, and performance in real water matrices for antibiotic degradation by Cu SACs. Finally, it highlights the key scientific challenges and future directions, including the precise construction of single-atom-cluster synergistic systems, integration of in situ/operando characterization with multiscale simulation, scalable synthesis and engineering lifetime validation, machine-learning-assisted high-throughput rational design, and holistic control of environmental risks throughout the treatment chain.